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December 07, 2010

Eliminate, Simplify, Integrate

BY Jovy J. Jader

Solving the waiting line problem

Waiting lines are part and parcel of our daily life. We wait in traffic, wait in line at a food buffet, and wait on hold when we call a company’s customer service.


Firms that find themselves catering to increased demand for their products and services try to maintain customer service quality through extra facilities aimed at reducing queues—a certified negative point in customer satisfaction.

Banks, for example, have set up “express” lanes for preferred clients. Government offices have priority lanes for senior citizens, while fast food outlets provide drive-thru windows that enable customers to order and pay without leaving their cars.

A waiting line gathers because the average time it takes for the operation to complete one transaction is longer than the average time it takes for the next client to pop up. To put it another way, a serving function (server) can’t cope with the arrival of so many customer orders (demand) at a given time.

Resolving this lag can be complicated in that demand can be infrequent: it may pick up at certain hours of the day, certain days of the month, or certain weeks in a year. For instance, a restaurant may be full with customers waiting to be seated at lunch hour but would almost be empty between meals.

A marketing company may have more orders at the end of the month as agents rush to meet quotas. And a bakery may see demand for its products surge during the holiday season. Conversely, firms that have sufficient facilities for moments of high demand may find themselves having too much idle capacity when customers start to come by in trickles.

The key to minimizing waiting lines lies in the Queuing Theory, a branch of operations research. Queuing theory determines whether to speed up the rate of servers, add more servers, or condition how customer orders arrive.

Steps to speed up on service rate may range from a simple throttling of a machine or increasing employee supervision to purchasing newer, higher capacity equipment or introducing new job descriptions for workers. Large, multi-national firms often rely on annual capacity planning to determine if new facilities are needed or if more people need to be hired to meet projected demand. Alternatively, companies may increase outsourcing from third-party organisations for the same purpose.

Adding more servers means installing more work stations that are similar to existing ones. This will enable firms to multiply their service processing rate for customers. We see this effect most visibly when a new queue opens up at a bank or at an airport immigration counter. Any new line significantly cuts waiting time.

Conditioning the arrival of customer orders entails managing demand trends. Instead of investing in service improvements, the firm offers incentives for customers to buy when demand is anticipated to be low. The opposite is also true; firms would charge higher prices when client count is on a climb to discourage orders from eating into capacity. Airlines, for example, would offer lower fares at “off-peak” periods to maximize flight occupancy while charging higher prices when demand outstrips their resources.

For all of the above options, there is the downside of extra expense. Upping service speed, whether by investing in better equipment or improved supervision, may result in higher maintenance costs, higher employee turnover and, in the former’s case, additional support personnel that the company must hire and train. Shaping demand influx via price incentives may result in lower revenue and the risk of selling at a loss.

How does one decide which strategy to develop? Firms can start by analyzing all aspects of their operations, from purchasing to manufacturing to logistics. Process flows would have to be drawn and work methods observed to calculate the actual time needed to serve an customer. Order histories would need to be recorded and used as bases for forecasts of future demand, with patterns and cycles included.

Such steps would provide the company with a map detailing the exact amount of time required to satisfy a customer request, which in turn can be used by managers to devise preliminary measures. Solving the waiting problem is a science that finds its most logical end in a doable equation.

Jovy Jader is a management consultant and regional speaker on Supply Chain Management. He has directed and implemented Supply Chain Management projects both local and international which have resulted to company-wide improvements in inventory, total cost, customer service, response time, quality, and on-time delivery. Mr. Jader was formerly with Procter & Gamble Philippines and Coopers & Lybrand/PricewaterhouseCoopers. Should you have questions or comments email to jovy@highimpactasia.com


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